Abstract
Parametric selection in machining processes is recently understood as a route to reducing waste generation in drilling activities and achieving a robust resource distribution in drilling activities. However, the selection methods dominant in the literature lack competence in reducing uncertainties and imprecision associated with the drilling process. The purpose of this research is to reduce the uncertainty and imprecision in previously analyzed data that used the analytic hierarchy process (AHP) method. This paper adjusts the uncertainty and imprecision by introducing a geometric mean-based fuzzy analytic hierarchy process. The selection method influences the drilling expert's preferences by imposing the fuzzy theory in a triangular member function that converts the crisp numerical values into fuzzy members and adequately suppresses the imprecision and uncertainty in the elements. The thrust force was positioned first in ranking with a FAHP method's weight of 0.415, which matched the literature value of 0.413 for the AHP method. It was found that the use of the FAHP method has corrected the imprecision and uncertainty introduced by the AHP method. It was found that the thrust force and torque were overestimated by or 0.48% and 3.95%, respectively and was accordingly corrected. Besides, no errors were found with the measurement of eccentricity response. Furthermore, the entry delamination, exit delamination and surface roughness were underestimated by -8.11%, -3.33% and -6.96%, respectively, and therefore corrected by the FAHP method. The usefulness of this effort is to enhance cost-effective decisions and the effectiveness in the distribution of scarce drilling resources.
Highlights
In the material removal area, it is conventional to recommend the best candidate parameter in a drilling operation through crisp numerical evaluation (Amini et al, 2017; Kulkarni and Ramachandran, 2018; Balaji et al, 2018; Agwa and Megahed, 2019; Odusoro and Oke, 2021)
fuzzy analytic hierarchy process (FAHP)-based multi-criteria drilling method entails a blend of theories and approaches to integrate drilling data and decision makers’ evaluations to create information necessary in drilling decision making
This research pursues the employment of the geometric-mean based fuzzy analytic hierarchy process to reduce the imprecision and uncertainty in the measurement of the data initially measured by the AHP method
Summary
In the material removal area, it is conventional to recommend the best candidate parameter in a drilling operation through crisp numerical evaluation (Amini et al, 2017; Kulkarni and Ramachandran, 2018; Balaji et al, 2018; Agwa and Megahed, 2019; Odusoro and Oke, 2021). The preferences of the drilling operator or process engineer are considered through a comparative matrix that weights one criterion against the other is introduced (Ayağ, 2007; Odusoro and Oke, 2021) In this setup, the inaccuracies introduced by the operator in measurements, equipmentrelated errors and several other imprecision and uncertainty are omitted in the MCDM results (Ayağ, 2007). The prevailing AHP model used to monitor the selection process of the drilling parameters for the carbon fibre reinforced plastic composites fails to reduce the imprecision and uncertainties in the AHP results (Odusoro and Oke, 2021). It helps pursue costeffective decisions and decision that optimizes the process variables within the limited frontier of drilling activity
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More From: International Journal of Industrial Engineering and Engineering Management
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